Overview

Brought to you by YData

Dataset statistics

Number of variables158
Number of observations10000
Missing cells42386
Missing cells (%)2.7%
Total size in memory6.9 MiB
Average record size in memory725.0 B

Variable types

Numeric74
Text7
Boolean77

Alerts

process_pmf_development_methodologies has constant value "agile development" Constant
project_prf_development_type_porting has constant value "False" Constant
people_prf_project_user_involvement_low has constant value "False" Constant
project_prf_development_type_not_defined has constant value "False" Constant
tech_tf_development_platform_hand_held has constant value "0.0" Constant
project_prf_relative_size_xxxl has constant value "False" Constant
tech_tf_architecture_multi_tier_client_server has constant value "False" Constant
tech_tf_client_server_not_applicable has constant value "False" Constant
tech_tf_type_of_server_proprietary_midrange has constant value "False" Constant
project_prf_application_type_top_financial application area has constant value "0.0" Constant
project_prf_application_type_top_client-server has constant value "0.0" Constant
project_prf_application_type_top_customer billing/relationship management has constant value "0.0" Constant
external_eef_data_quality_rating_c_lang is highly imbalanced (79.9%) Imbalance
external_eef_data_quality_rating_d is highly imbalanced (82.3%) Imbalance
project_prf_development_type_other is highly imbalanced (99.1%) Imbalance
project_prf_development_type_poc is highly imbalanced (99.7%) Imbalance
project_prf_development_type_re_development is highly imbalanced (92.9%) Imbalance
tech_tf_development_platform_mr is highly imbalanced (61.4%) Imbalance
tech_tf_development_platform_proprietary is highly imbalanced (96.3%) Imbalance
tech_tf_language_type_2gl is highly imbalanced (99.1%) Imbalance
tech_tf_language_type_5gl is highly imbalanced (97.9%) Imbalance
tech_tf_language_type_apg is highly imbalanced (85.0%) Imbalance
project_prf_relative_size_l is highly imbalanced (79.7%) Imbalance
project_prf_relative_size_nan is highly imbalanced (77.1%) Imbalance
project_prf_relative_size_xl is highly imbalanced (96.8%) Imbalance
project_prf_relative_size_xs is highly imbalanced (54.3%) Imbalance
project_prf_relative_size_xxl is highly imbalanced (99.4%) Imbalance
project_prf_relative_size_xxs is highly imbalanced (68.9%) Imbalance
project_prf_case_tool_used_don_t_know is highly imbalanced (98.6%) Imbalance
project_prf_case_tool_used_no is highly imbalanced (68.9%) Imbalance
project_prf_case_tool_used_yes is highly imbalanced (55.6%) Imbalance
tech_tf_architecture_multi_tier_with_web_interface is highly imbalanced (94.1%) Imbalance
tech_tf_architecture_multi_tier_with_web_public_interface is highly imbalanced (73.1%) Imbalance
tech_tf_architecture_stand_alone is highly imbalanced (97.4%) Imbalance
tech_tf_client_server_don_t_know is highly imbalanced (96.4%) Imbalance
tech_tf_client_server_no is highly imbalanced (63.0%) Imbalance
tech_tf_type_of_server_back_end is highly imbalanced (98.7%) Imbalance
tech_tf_type_of_server_client_server is highly imbalanced (60.4%) Imbalance
tech_tf_type_of_server_lan_based is highly imbalanced (98.8%) Imbalance
tech_tf_type_of_server_mainframe is highly imbalanced (86.2%) Imbalance
tech_tf_type_of_server_multi_tier_with_web_public_interface is highly imbalanced (94.6%) Imbalance
tech_tf_type_of_server_standalone is highly imbalanced (92.7%) Imbalance
tech_tf_type_of_server_unix is highly imbalanced (97.7%) Imbalance
tech_tf_type_of_server_webserver is highly imbalanced (99.7%) Imbalance
tech_tf_dbms_used_no is highly imbalanced (95.5%) Imbalance
people_prf_project_user_involvement_best is highly imbalanced (99.7%) Imbalance
people_prf_project_user_involvement_don_t_know is highly imbalanced (99.3%) Imbalance
people_prf_project_user_involvement_nan is highly imbalanced (91.8%) Imbalance
people_prf_project_user_involvement_no is highly imbalanced (99.9%) Imbalance
people_prf_project_user_involvement_yes is highly imbalanced (94.6%) Imbalance
project_prf_currency_multiple_yes_1_000 is highly imbalanced (99.6%) Imbalance
project_prf_currency_multiple_yes_10_000 is highly imbalanced (99.7%) Imbalance
tech_tf_clientserver_description_browser_server_architecture has 190 (1.9%) missing values Missing
tech_tf_clientserver_description_client_server has 167 (1.7%) missing values Missing
tech_tf_clientserver_description_client_presentation has 189 (1.9%) missing values Missing
tech_tf_clientserver_description_client_presentation_processing has 227 (2.3%) missing values Missing
tech_tf_clientserver_description_client_server_architecture has 192 (1.9%) missing values Missing
tech_tf_clientserver_description_client_server_architecture_p2p has 190 (1.9%) missing values Missing
tech_tf_clientserver_description_nan has 166 (1.7%) missing values Missing
tech_tf_clientserver_description_server_processing has 166 (1.7%) missing values Missing
tech_tf_clientserver_description_stand_alone has 207 (2.1%) missing values Missing
tech_tf_clientserver_description_web has 189 (1.9%) missing values Missing
project_prf_application_type_top_management of licences and permits has 269 (2.7%) missing values Missing
project_prf_application_type_top_software for machine control has 208 (2.1%) missing values Missing
project_prf_application_type_top_data warehouse system has 215 (2.1%) missing values Missing
project_prf_application_type_top_management or performance reporting has 201 (2.0%) missing values Missing
tech_tf_development_platform_hand_held has 353 (3.5%) missing values Missing
project_prf_application_type_top_transaction/production system has 9861 (98.6%) missing values Missing
project_prf_application_type_top_financial application area has 9812 (98.1%) missing values Missing
project_prf_application_type_top_client-server has 9804 (98.0%) missing values Missing
project_prf_application_type_top_customer billing/relationship management has 9780 (97.8%) missing values Missing
tech_tf_clientserver_description_client_presentation is highly skewed (γ1 = 70.02856342) Skewed
tech_tf_clientserver_description_client_presentation_processing is highly skewed (γ1 = 27.36787303) Skewed
tech_tf_clientserver_description_client_server_architecture is highly skewed (γ1 = 20.5807358) Skewed
tech_tf_clientserver_description_client_server_architecture_p2p is highly skewed (γ1 = 99.04544412) Skewed
tech_tf_clientserver_description_server_processing is highly skewed (γ1 = 57.23634912) Skewed
tech_tf_clientserver_description_stand_alone is highly skewed (γ1 = 22.06357108) Skewed
project_prf_normalised_level_1_pdr_ufp has unique values Unique
project_prf_normalised_pdr_ufp has unique values Unique
process_pmf_docs has 252 (2.5%) zeros Zeros
tech_tf_tools_used has 6240 (62.4%) zeros Zeros
project_prf_application_group_business_application has 3507 (35.1%) zeros Zeros
project_prf_application_group_infrastructure_software has 9913 (99.1%) zeros Zeros
project_prf_application_group_mathematically_intensive_application has 9391 (93.9%) zeros Zeros
project_prf_application_group_nan has 7518 (75.2%) zeros Zeros
project_prf_application_group_real_time_application has 9516 (95.2%) zeros Zeros
tech_tf_clientserver_description_browser_server_architecture has 9721 (97.2%) zeros Zeros
tech_tf_clientserver_description_client_server has 9673 (96.7%) zeros Zeros
tech_tf_clientserver_description_client_presentation has 9809 (98.1%) zeros Zeros
tech_tf_clientserver_description_client_presentation_processing has 9760 (97.6%) zeros Zeros
tech_tf_clientserver_description_client_server_architecture has 9785 (97.9%) zeros Zeros
tech_tf_clientserver_description_client_server_architecture_p2p has 9809 (98.1%) zeros Zeros
tech_tf_clientserver_description_nan has 363 (3.6%) zeros Zeros
tech_tf_clientserver_description_server_processing has 9831 (98.3%) zeros Zeros
tech_tf_clientserver_description_stand_alone has 9773 (97.7%) zeros Zeros
tech_tf_clientserver_description_web has 9747 (97.5%) zeros Zeros
external_eef_organisation_type_top_insurance has 8584 (85.8%) zeros Zeros
external_eef_organisation_type_top_medical and health care has 8580 (85.8%) zeros Zeros
external_eef_organisation_type_top_manufacturing has 8661 (86.6%) zeros Zeros
external_eef_organisation_type_top_telecommunications has 8615 (86.2%) zeros Zeros
external_eef_organisation_type_top_government has 8954 (89.5%) zeros Zeros
external_eef_organisation_type_top_nan has 9034 (90.3%) zeros Zeros
external_eef_organisation_type_top_communications has 9239 (92.4%) zeros Zeros
external_eef_organisation_type_top_banking has 9436 (94.4%) zeros Zeros
external_eef_organisation_type_top_computers & software has 9767 (97.7%) zeros Zeros
external_eef_organisation_type_top_defence has 9795 (98.0%) zeros Zeros
external_eef_organisation_type_top_public administration has 9824 (98.2%) zeros Zeros
external_eef_organisation_type_top_aerospace / automotive has 9806 (98.1%) zeros Zeros
external_eef_organisation_type_top_transport & storage has 9826 (98.3%) zeros Zeros
external_eef_organisation_type_top_financial, property & business services has 9880 (98.8%) zeros Zeros
external_eef_organisation_type_top_education institution has 9873 (98.7%) zeros Zeros
external_eef_organisation_type_top_community services has 9879 (98.8%) zeros Zeros
external_eef_organisation_type_top_electricity, gas, water has 9884 (98.8%) zeros Zeros
external_eef_organisation_type_top_logistics has 9910 (99.1%) zeros Zeros
external_eef_organisation_type_top_wholesale & retail trade has 9899 (99.0%) zeros Zeros
external_eef_organisation_type_top_telecommunication has 9912 (99.1%) zeros Zeros
external_eef_organisation_type_other has 9495 (95.0%) zeros Zeros
project_prf_application_type_top_financial transaction process/accounting has 8392 (83.9%) zeros Zeros
project_prf_application_type_top_not recorded has 8578 (85.8%) zeros Zeros
project_prf_application_type_top_nan has 8919 (89.2%) zeros Zeros
project_prf_application_type_top_unknown has 9297 (93.0%) zeros Zeros
project_prf_application_type_top_customer relationship management has 9452 (94.5%) zeros Zeros
project_prf_application_type_top_relatively complex application has 9551 (95.5%) zeros Zeros
project_prf_application_type_top_workflow support & management has 9644 (96.4%) zeros Zeros
project_prf_application_type_top_business application has 9685 (96.9%) zeros Zeros
project_prf_application_type_top_embedded system/real_time application has 9746 (97.5%) zeros Zeros
project_prf_application_type_top_online. esales has 9778 (97.8%) zeros Zeros
project_prf_application_type_top_management of licences and permits has 9526 (95.3%) zeros Zeros
project_prf_application_type_top_online analysis and reporting has 9767 (97.7%) zeros Zeros
project_prf_application_type_top_catalogue/register of things or events has 9836 (98.4%) zeros Zeros
project_prf_application_type_top_software for machine control has 9634 (96.3%) zeros Zeros
project_prf_application_type_top_document management has 9857 (98.6%) zeros Zeros
project_prf_application_type_top_electronic data interchange has 9841 (98.4%) zeros Zeros
project_prf_application_type_top_management information system has 9824 (98.2%) zeros Zeros
project_prf_application_type_top_data warehouse system has 9686 (96.9%) zeros Zeros
project_prf_application_type_top_stock control & order processing has 9888 (98.9%) zeros Zeros
project_prf_application_type_top_management or performance reporting has 9699 (97.0%) zeros Zeros
project_prf_application_type_other has 7517 (75.2%) zeros Zeros
tech_tf_development_platform_hand_held has 9647 (96.5%) zeros Zeros
project_prf_application_type_top_transaction/production system has 118 (1.2%) zeros Zeros
project_prf_application_type_top_financial application area has 188 (1.9%) zeros Zeros
project_prf_application_type_top_client-server has 196 (2.0%) zeros Zeros
project_prf_application_type_top_customer billing/relationship management has 220 (2.2%) zeros Zeros

Reproduction

Analysis started2025-06-03 13:35:12.568588
Analysis finished2025-06-03 13:35:13.588859
Duration1.02 second
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

isbsg_project_id
Real number (ℝ)

Distinct3571
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21344.06
Minimum10003
Maximum32767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:13.796289image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum10003
5-th percentile11148
Q115631
median21296
Q326949.5
95-th percentile31750
Maximum32767
Range22764
Interquartile range (IQR)11318.5

Descriptive statistics

Standard deviation6580.58918
Coefficient of variation (CV)0.3083100956
Kurtosis-1.183008815
Mean21344.06
Median Absolute Deviation (MAD)5659
Skewness0.02045276715
Sum213440600
Variance43304153.95
MonotonicityNot monotonic
2025-06-03T14:35:14.000396image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24020 10
 
0.1%
26542 9
 
0.1%
15696 9
 
0.1%
13946 9
 
0.1%
17161 9
 
0.1%
10486 9
 
0.1%
26676 9
 
0.1%
26695 9
 
0.1%
30754 9
 
0.1%
11532 9
 
0.1%
Other values (3561) 9909
99.1%
ValueCountFrequency (%)
10003 2
 
< 0.1%
10019 7
0.1%
10028 5
0.1%
10033 3
< 0.1%
10046 5
0.1%
ValueCountFrequency (%)
32767 4
< 0.1%
32762 3
< 0.1%
32756 2
< 0.1%
32754 3
< 0.1%
32753 3
< 0.1%
Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.6768
Minimum1989
Maximum2015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:14.162261image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1989
5-th percentile1997
Q12009
median2013
Q32015
95-th percentile2015
Maximum2015
Range26
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.882244626
Coefficient of variation (CV)0.002925504798
Kurtosis3.099714155
Mean2010.6768
Median Absolute Deviation (MAD)2
Skewness-1.858532019
Sum20106768
Variance34.60080184
MonotonicityNot monotonic
2025-06-03T14:35:14.350406image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2015 3048
30.5%
2014 1570
15.7%
2013 990
 
9.9%
2012 726
 
7.3%
2011 570
 
5.7%
2010 405
 
4.0%
2009 358
 
3.6%
2008 303
 
3.0%
2007 261
 
2.6%
2006 214
 
2.1%
Other values (17) 1555
15.6%
ValueCountFrequency (%)
1989 149
1.5%
1990 29
 
0.3%
1991 37
 
0.4%
1992 29
 
0.3%
1993 47
 
0.5%
ValueCountFrequency (%)
2015 3048
30.5%
2014 1570
15.7%
2013 990
 
9.9%
2012 726
 
7.3%
2011 570
 
5.7%
Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:14.536391image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length23
Median length18
Mean length11.7623
Min length6

Characters and Unicode

Total characters117623
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmanufacturing
2nd rowmedical & health care
3rd rowinsurance
4th rowmedical & health care
5th rowmedical & health care
ValueCountFrequency (%)
government 1733
11.7%
1597
10.8%
manufacturing 1496
10.1%
insurance 1302
 
8.8%
medical 1138
 
7.7%
health 1138
 
7.7%
care 1138
 
7.7%
missing 1071
 
7.2%
banking 523
 
3.5%
defence 435
 
2.9%
Other values (14) 3274
22.1%
2025-06-03T14:35:15.004484image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 13650
11.6%
e 12705
10.8%
i 10624
 
9.0%
a 9872
 
8.4%
c 7870
 
6.7%
r 7477
 
6.4%
s 6638
 
5.6%
t 6551
 
5.6%
u 5409
 
4.6%
g 5207
 
4.4%
Other values (15) 31620
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 117623
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 13650
11.6%
e 12705
10.8%
i 10624
 
9.0%
a 9872
 
8.4%
c 7870
 
6.7%
r 7477
 
6.4%
s 6638
 
5.6%
t 6551
 
5.6%
u 5409
 
4.6%
g 5207
 
4.4%
Other values (15) 31620
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 117623
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 13650
11.6%
e 12705
10.8%
i 10624
 
9.0%
a 9872
 
8.4%
c 7870
 
6.7%
r 7477
 
6.4%
s 6638
 
5.6%
t 6551
 
5.6%
u 5409
 
4.6%
g 5207
 
4.4%
Other values (15) 31620
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 117623
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 13650
11.6%
e 12705
10.8%
i 10624
 
9.0%
a 9872
 
8.4%
c 7870
 
6.7%
r 7477
 
6.4%
s 6638
 
5.6%
t 6551
 
5.6%
u 5409
 
4.6%
g 5207
 
4.4%
Other values (15) 31620
26.9%
Distinct73
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:15.284195image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length32
Median length30
Mean length5.254
Min length2

Characters and Unicode

Total characters52540
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st rowpl/i
2nd rowsiebel
3rd rowpl/i
4th rowjava
5th rowjava
ValueCountFrequency (%)
java 3655
34.4%
cobol 1118
 
10.5%
dotnet 689
 
6.5%
pl/i 576
 
5.4%
visual 469
 
4.4%
csharp 447
 
4.2%
basic 433
 
4.1%
abap 420
 
4.0%
c_lang 334
 
3.1%
oracle 306
 
2.9%
Other values (76) 2165
20.4%
2025-06-03T14:35:15.724518image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10965
20.9%
l 4263
 
8.1%
v 4159
 
7.9%
o 4111
 
7.8%
j 3679
 
7.0%
c 3377
 
6.4%
p 2770
 
5.3%
b 2441
 
4.6%
s 2297
 
4.4%
e 2108
 
4.0%
Other values (26) 12370
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 52540
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 10965
20.9%
l 4263
 
8.1%
v 4159
 
7.9%
o 4111
 
7.8%
j 3679
 
7.0%
c 3377
 
6.4%
p 2770
 
5.3%
b 2441
 
4.6%
s 2297
 
4.4%
e 2108
 
4.0%
Other values (26) 12370
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 52540
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 10965
20.9%
l 4263
 
8.1%
v 4159
 
7.9%
o 4111
 
7.8%
j 3679
 
7.0%
c 3377
 
6.4%
p 2770
 
5.3%
b 2441
 
4.6%
s 2297
 
4.4%
e 2108
 
4.0%
Other values (26) 12370
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 52540
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 10965
20.9%
l 4263
 
8.1%
v 4159
 
7.9%
o 4111
 
7.8%
j 3679
 
7.0%
c 3377
 
6.4%
p 2770
 
5.3%
b 2441
 
4.6%
s 2297
 
4.4%
e 2108
 
4.0%
Other values (26) 12370
23.5%
Distinct1087
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.9096
Minimum2
Maximum2292
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:15.920964image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q145
median136
Q3311
95-th percentile765
Maximum2292
Range2290
Interquartile range (IQR)266

Descriptive statistics

Standard deviation264.2551511
Coefficient of variation (CV)1.16458339
Kurtosis7.121614516
Mean226.9096
Median Absolute Deviation (MAD)109
Skewness2.260174845
Sum2269096
Variance69830.78491
MonotonicityNot monotonic
2025-06-03T14:35:16.100128image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 149
 
1.5%
5 105
 
1.1%
4 95
 
0.9%
2 95
 
0.9%
6 90
 
0.9%
9 88
 
0.9%
11 77
 
0.8%
8 76
 
0.8%
7 75
 
0.8%
16 68
 
0.7%
Other values (1077) 9082
90.8%
ValueCountFrequency (%)
2 95
0.9%
3 149
1.5%
4 95
0.9%
5 105
1.1%
6 90
0.9%
ValueCountFrequency (%)
2292 1
< 0.1%
2253 1
< 0.1%
2183 1
< 0.1%
2166 1
< 0.1%
2089 1
< 0.1%
Distinct5612
Distinct (%)56.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3686.9502
Minimum4
Maximum42794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:16.405514image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile55
Q1627.75
median2044.5
Q35021.25
95-th percentile12921.65
Maximum42794
Range42790
Interquartile range (IQR)4393.5

Descriptive statistics

Standard deviation4563.841473
Coefficient of variation (CV)1.237836484
Kurtosis8.833672918
Mean3686.9502
Median Absolute Deviation (MAD)1711
Skewness2.464893452
Sum36869502
Variance20828648.99
MonotonicityNot monotonic
2025-06-03T14:35:16.582956image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 31
 
0.3%
4 24
 
0.2%
6 20
 
0.2%
8 20
 
0.2%
11 19
 
0.2%
9 17
 
0.2%
16 15
 
0.1%
12 13
 
0.1%
21 13
 
0.1%
39 13
 
0.1%
Other values (5602) 9815
98.2%
ValueCountFrequency (%)
4 24
0.2%
5 31
0.3%
6 20
0.2%
7 12
 
0.1%
8 20
0.2%
ValueCountFrequency (%)
42794 1
< 0.1%
41064 1
< 0.1%
40441 1
< 0.1%
38780 1
< 0.1%
38185 1
< 0.1%
Distinct5738
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4141.9318
Minimum2
Maximum64834
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:16.762546image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile33
Q1528
median2069
Q35580.25
95-th percentile15127.25
Maximum64834
Range64832
Interquartile range (IQR)5052.25

Descriptive statistics

Standard deviation5518.916146
Coefficient of variation (CV)1.332449787
Kurtosis10.69415504
Mean4141.9318
Median Absolute Deviation (MAD)1839
Skewness2.67663741
Sum41419318
Variance30458435.42
MonotonicityNot monotonic
2025-06-03T14:35:16.944364image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 52
 
0.5%
3 40
 
0.4%
4 28
 
0.3%
5 26
 
0.3%
7 24
 
0.2%
6 21
 
0.2%
11 19
 
0.2%
14 18
 
0.2%
8 18
 
0.2%
36 18
 
0.2%
Other values (5728) 9736
97.4%
ValueCountFrequency (%)
2 52
0.5%
3 40
0.4%
4 28
0.3%
5 26
0.3%
6 21
0.2%
ValueCountFrequency (%)
64834 1
< 0.1%
54549 1
< 0.1%
52596 1
< 0.1%
50993 1
< 0.1%
46963 1
< 0.1%

project_prf_normalised_level_1_pdr_ufp
Real number (ℝ)

Unique 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.63635107
Minimum0.10002408
Maximum493.98682
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:17.129421image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.10002408
5-th percentile0.751207293
Q16.877582075
median21.459283
Q350.3166895
95-th percentile125.547515
Maximum493.98682
Range493.8867959
Interquartile range (IQR)43.43910743

Descriptive statistics

Standard deviation43.81402812
Coefficient of variation (CV)1.19591681
Kurtosis10.0673091
Mean36.63635107
Median Absolute Deviation (MAD)17.3088466
Skewness2.489105848
Sum366363.5107
Variance1919.66906
MonotonicityNot monotonic
2025-06-03T14:35:17.317330image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.136001 1
 
< 0.1%
3.418775 1
 
< 0.1%
22.305004 1
 
< 0.1%
47.02558 1
 
< 0.1%
7.7405777 1
 
< 0.1%
6.0905523 1
 
< 0.1%
32.359634 1
 
< 0.1%
165.7202 1
 
< 0.1%
10.814537 1
 
< 0.1%
14.496101 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
0.10002408 1
< 0.1%
0.10003579 1
< 0.1%
0.10006147 1
< 0.1%
0.10051391 1
< 0.1%
0.10064977 1
< 0.1%
ValueCountFrequency (%)
493.98682 1
< 0.1%
488.25894 1
< 0.1%
471.1346 1
< 0.1%
393.01562 1
< 0.1%
391.7724 1
< 0.1%

project_prf_normalised_pdr_ufp
Real number (ℝ)

Unique 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.0951462
Minimum0.10001235
Maximum524.9843
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:17.489557image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.10001235
5-th percentile0.596217765
Q16.2714609
median20.480635
Q350.83241375
95-th percentile128.8462225
Maximum524.9843
Range524.8842876
Interquartile range (IQR)44.56095285

Descriptive statistics

Standard deviation45.91171285
Coefficient of variation (CV)1.237674401
Kurtosis10.60411757
Mean37.0951462
Median Absolute Deviation (MAD)17.200996
Skewness2.570527298
Sum370951.462
Variance2107.885377
MonotonicityNot monotonic
2025-06-03T14:35:17.700671image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.700681 1
 
< 0.1%
2.371943 1
 
< 0.1%
25.159613 1
 
< 0.1%
54.149612 1
 
< 0.1%
9.362135 1
 
< 0.1%
8.033995 1
 
< 0.1%
23.296803 1
 
< 0.1%
174.04132 1
 
< 0.1%
12.614067 1
 
< 0.1%
14.091162 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
0.10001235 1
< 0.1%
0.10005237 1
< 0.1%
0.10006483 1
< 0.1%
0.10008786 1
< 0.1%
0.100270055 1
< 0.1%
ValueCountFrequency (%)
524.9843 1
< 0.1%
498.89432 1
< 0.1%
497.51907 1
< 0.1%
432.4285 1
< 0.1%
415.93933 1
< 0.1%
Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.18291485
Minimum4.352757 × 10-6
Maximum293.08795
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:17.883675image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum4.352757 × 10-6
5-th percentile1.19786814
Q17.862614
median21.181595
Q346.0576145
95-th percentile106.9413632
Maximum293.08795
Range293.0879456
Interquartile range (IQR)38.1950005

Descriptive statistics

Standard deviation35.95406985
Coefficient of variation (CV)1.0835115
Kurtosis5.839262982
Mean33.18291485
Median Absolute Deviation (MAD)15.8338479
Skewness2.062463232
Sum331829.1485
Variance1292.695139
MonotonicityNot monotonic
2025-06-03T14:35:18.089103image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.8108835 2
 
< 0.1%
98.51386 1
 
< 0.1%
84.90398 1
 
< 0.1%
25.770863 1
 
< 0.1%
49.66178 1
 
< 0.1%
35.91762 1
 
< 0.1%
189.8083 1
 
< 0.1%
42.58118 1
 
< 0.1%
8.052147 1
 
< 0.1%
5.377269 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
4.352757 × 10-61
< 0.1%
0.000259596 1
< 0.1%
0.0010564977 1
< 0.1%
0.0012062693 1
< 0.1%
0.0012111719 1
< 0.1%
ValueCountFrequency (%)
293.08795 1
< 0.1%
290.08167 1
< 0.1%
287.46378 1
< 0.1%
283.59283 1
< 0.1%
269.95605 1
< 0.1%
Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.225756855
Minimum0.13142453
Maximum50.576675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:18.262973image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.13142453
5-th percentile1.333830585
Q13.686948575
median6.72608565
Q311.17733575
95-th percentile19.99061615
Maximum50.576675
Range50.44525047
Interquartile range (IQR)7.490387175

Descriptive statistics

Standard deviation6.131121503
Coefficient of variation (CV)0.7453565199
Kurtosis2.918499387
Mean8.225756855
Median Absolute Deviation (MAD)3.50133435
Skewness1.450689989
Sum82257.56855
Variance37.59065089
MonotonicityNot monotonic
2025-06-03T14:35:18.460660image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.248429 2
 
< 0.1%
0.5490756 1
 
< 0.1%
3.0750308 1
 
< 0.1%
6.908718 1
 
< 0.1%
3.8669133 1
 
< 0.1%
21.549868 1
 
< 0.1%
4.3568096 1
 
< 0.1%
0.6841554 1
 
< 0.1%
2.0032315 1
 
< 0.1%
11.489345 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
0.13142453 1
< 0.1%
0.14001884 1
< 0.1%
0.14957522 1
< 0.1%
0.15957922 1
< 0.1%
0.16427469 1
< 0.1%
ValueCountFrequency (%)
50.576675 1
< 0.1%
48.355022 1
< 0.1%
45.17002 1
< 0.1%
44.445194 1
< 0.1%
43.555637 1
< 0.1%
Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:18.601083image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.5643
Min length1

Characters and Unicode

Total characters45643
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row71_80
2nd row71_80
3rd row101+
4th row91_100
5th row101+
ValueCountFrequency (%)
101 3893
38.9%
91_100 2684
26.8%
71_80 836
 
8.4%
5_8 434
 
4.3%
21_30 396
 
4.0%
2 330
 
3.3%
9_14 272
 
2.7%
31_40 205
 
2.1%
3_4 190
 
1.9%
15_20 178
 
1.8%
Other values (5) 582
 
5.8%
2025-06-03T14:35:18.886320image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15623
34.2%
0 11381
24.9%
_ 5700
 
12.5%
+ 3893
 
8.5%
9 3097
 
6.8%
8 1411
 
3.1%
7 1005
 
2.2%
2 904
 
2.0%
4 818
 
1.8%
5 807
 
1.8%
Other values (2) 1004
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45643
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 15623
34.2%
0 11381
24.9%
_ 5700
 
12.5%
+ 3893
 
8.5%
9 3097
 
6.8%
8 1411
 
3.1%
7 1005
 
2.2%
2 904
 
2.0%
4 818
 
1.8%
5 807
 
1.8%
Other values (2) 1004
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45643
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 15623
34.2%
0 11381
24.9%
_ 5700
 
12.5%
+ 3893
 
8.5%
9 3097
 
6.8%
8 1411
 
3.1%
7 1005
 
2.2%
2 904
 
2.0%
4 818
 
1.8%
5 807
 
1.8%
Other values (2) 1004
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45643
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 15623
34.2%
0 11381
24.9%
_ 5700
 
12.5%
+ 3893
 
8.5%
9 3097
 
6.8%
8 1411
 
3.1%
7 1005
 
2.2%
2 904
 
2.0%
4 818
 
1.8%
5 807
 
1.8%
Other values (2) 1004
 
2.2%

project_prf_max_team_size
Real number (ℝ)

Distinct9999
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.47676346
Minimum0.30892137
Maximum133.48668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:19.092098image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.30892137
5-th percentile2.177861945
Q16.6323634
median12.395476
Q321.146731
95-th percentile38.68165775
Maximum133.48668
Range133.1777586
Interquartile range (IQR)14.5143676

Descriptive statistics

Standard deviation12.12773938
Coefficient of variation (CV)0.7836095329
Kurtosis4.450331555
Mean15.47676346
Median Absolute Deviation (MAD)6.755897
Skewness1.641465356
Sum154767.6346
Variance147.0820626
MonotonicityNot monotonic
2025-06-03T14:35:19.285810image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.388292 2
 
< 0.1%
2.893684 1
 
< 0.1%
9.671537 1
 
< 0.1%
21.386906 1
 
< 0.1%
17.411036 1
 
< 0.1%
3.482389 1
 
< 0.1%
5.2900295 1
 
< 0.1%
23.252901 1
 
< 0.1%
73.68521 1
 
< 0.1%
16.246553 1
 
< 0.1%
Other values (9989) 9989
99.9%
ValueCountFrequency (%)
0.30892137 1
< 0.1%
0.33520854 1
< 0.1%
0.33738205 1
< 0.1%
0.38181192 1
< 0.1%
0.3887034 1
< 0.1%
ValueCountFrequency (%)
133.48668 1
< 0.1%
115.152756 1
< 0.1%
88.957924 1
< 0.1%
87.176506 1
< 0.1%
86.77155 1
< 0.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:19.443792image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters170000
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowagile development
2nd rowagile development
3rd rowagile development
4th rowagile development
5th rowagile development
ValueCountFrequency (%)
agile 10000
50.0%
development 10000
50.0%
2025-06-03T14:35:19.735007image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 170000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 40000
23.5%
l 20000
11.8%
a 10000
 
5.9%
g 10000
 
5.9%
i 10000
 
5.9%
10000
 
5.9%
d 10000
 
5.9%
v 10000
 
5.9%
o 10000
 
5.9%
p 10000
 
5.9%
Other values (3) 30000
17.6%

process_pmf_docs
Real number (ℝ)

Zeros 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4644
Minimum0
Maximum20
Zeros252
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:19.908916image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q36
95-th percentile10
Maximum20
Range20
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.122484208
Coefficient of variation (CV)0.6994185575
Kurtosis2.300553915
Mean4.4644
Median Absolute Deviation (MAD)2
Skewness1.296470852
Sum44644
Variance9.749907631
MonotonicityNot monotonic
2025-06-03T14:35:20.082507image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 1580
15.8%
3 1578
15.8%
4 1347
13.5%
1 1183
11.8%
5 1124
11.2%
6 799
8.0%
7 622
 
6.2%
8 460
 
4.6%
9 323
 
3.2%
0 252
 
2.5%
Other values (11) 732
7.3%
ValueCountFrequency (%)
0 252
 
2.5%
1 1183
11.8%
2 1580
15.8%
3 1578
15.8%
4 1347
13.5%
ValueCountFrequency (%)
20 15
0.1%
19 11
0.1%
18 9
 
0.1%
17 12
0.1%
16 23
0.2%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:20.234642image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length114
Median length7
Mean length7.0155
Min length7

Characters and Unicode

Total characters70155
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowMissing
2nd rowMissing
3rd rowMissing
4th rowMissing
5th rowMissing
ValueCountFrequency (%)
missing 9998
99.8%
data 3
 
< 0.1%
3
 
< 0.1%
entry 2
 
< 0.1%
validation 2
 
< 0.1%
run 2
 
< 0.1%
a 2
 
< 0.1%
computer_human 2
 
< 0.1%
interface 2
 
< 0.1%
retrieval 1
 
< 0.1%
Other values (4) 4
 
< 0.1%
2025-06-03T14:35:20.526028image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 20005
28.5%
s 19999
28.5%
n 10010
14.3%
M 9998
14.3%
g 9998
14.3%
21
 
< 0.1%
a 18
 
< 0.1%
t 16
 
< 0.1%
e 15
 
< 0.1%
r 14
 
< 0.1%
Other values (17) 61
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70155
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 20005
28.5%
s 19999
28.5%
n 10010
14.3%
M 9998
14.3%
g 9998
14.3%
21
 
< 0.1%
a 18
 
< 0.1%
t 16
 
< 0.1%
e 15
 
< 0.1%
r 14
 
< 0.1%
Other values (17) 61
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70155
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 20005
28.5%
s 19999
28.5%
n 10010
14.3%
M 9998
14.3%
g 9998
14.3%
21
 
< 0.1%
a 18
 
< 0.1%
t 16
 
< 0.1%
e 15
 
< 0.1%
r 14
 
< 0.1%
Other values (17) 61
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70155
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 20005
28.5%
s 19999
28.5%
n 10010
14.3%
M 9998
14.3%
g 9998
14.3%
21
 
< 0.1%
a 18
 
< 0.1%
t 16
 
< 0.1%
e 15
 
< 0.1%
r 14
 
< 0.1%
Other values (17) 61
 
0.1%
Distinct71
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:20.692174image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length162
Median length101
Mean length56.802
Min length8

Characters and Unicode

Total characters568020
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsecurity/authentication
2nd rowdatabase server; file/print server; html/web server; mail server; security/authentication
3rd rowdatabase server; multi_user legacy application; security/authentication
4th rowdatabase server; security/authentication
5th rowdatabase server; ftp server; html/web server; mail server; security/authentication
ValueCountFrequency (%)
server 22257
39.0%
database 8124
 
14.2%
security/authentication 5449
 
9.6%
html/web 5116
 
9.0%
application 1950
 
3.4%
file/print 1883
 
3.3%
multi_user 1878
 
3.3%
legacy 1878
 
3.3%
mail 1800
 
3.2%
object/component 1680
 
2.9%
Other values (27) 5021
 
8.8%
2025-06-03T14:35:21.245612image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 80933
14.2%
r 54626
 
9.6%
47036
 
8.3%
t 46302
 
8.2%
a 45227
 
8.0%
s 42177
 
7.4%
i 30114
 
5.3%
v 22565
 
4.0%
n 20475
 
3.6%
; 20251
 
3.6%
Other values (24) 158314
27.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 568020
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 80933
14.2%
r 54626
 
9.6%
47036
 
8.3%
t 46302
 
8.2%
a 45227
 
8.0%
s 42177
 
7.4%
i 30114
 
5.3%
v 22565
 
4.0%
n 20475
 
3.6%
; 20251
 
3.6%
Other values (24) 158314
27.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 568020
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 80933
14.2%
r 54626
 
9.6%
47036
 
8.3%
t 46302
 
8.2%
a 45227
 
8.0%
s 42177
 
7.4%
i 30114
 
5.3%
v 22565
 
4.0%
n 20475
 
3.6%
; 20251
 
3.6%
Other values (24) 158314
27.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 568020
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 80933
14.2%
r 54626
 
9.6%
47036
 
8.3%
t 46302
 
8.2%
a 45227
 
8.0%
s 42177
 
7.4%
i 30114
 
5.3%
v 22565
 
4.0%
n 20475
 
3.6%
; 20251
 
3.6%
Other values (24) 158314
27.9%

tech_tf_tools_used
Real number (ℝ)

Zeros 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4636
Minimum0
Maximum10
Zeros6240
Zeros (%)62.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:21.395586image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.716949249
Coefficient of variation (CV)1.85634685
Kurtosis3.382897659
Mean1.4636
Median Absolute Deviation (MAD)0
Skewness2.099948683
Sum14636
Variance7.381813221
MonotonicityNot monotonic
2025-06-03T14:35:21.547254image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 6240
62.4%
1 1218
 
12.2%
2 618
 
6.2%
10 513
 
5.1%
3 409
 
4.1%
4 289
 
2.9%
5 218
 
2.2%
6 175
 
1.8%
7 117
 
1.2%
8 117
 
1.2%
ValueCountFrequency (%)
0 6240
62.4%
1 1218
 
12.2%
2 618
 
6.2%
3 409
 
4.1%
4 289
 
2.9%
ValueCountFrequency (%)
10 513
5.1%
9 86
 
0.9%
8 117
 
1.2%
7 117
 
1.2%
6 175
 
1.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6493
Minimum0
Maximum1
Zeros3507
Zeros (%)35.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:21.685529image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4772130376
Coefficient of variation (CV)0.7349654052
Kurtosis-1.608644163
Mean0.6493
Median Absolute Deviation (MAD)0
Skewness-0.6258415182
Sum6493
Variance0.2277322832
MonotonicityNot monotonic
2025-06-03T14:35:21.819951image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 6493
64.9%
0 3507
35.1%
ValueCountFrequency (%)
0 3507
35.1%
1 6493
64.9%
ValueCountFrequency (%)
1 6493
64.9%
0 3507
35.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0087
Minimum0
Maximum1
Zeros9913
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:21.946202image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0928718069
Coefficient of variation (CV)10.67492033
Kurtosis110.0069008
Mean0.0087
Median Absolute Deviation (MAD)0
Skewness10.58229179
Sum87
Variance0.008625172517
MonotonicityNot monotonic
2025-06-03T14:35:22.072668image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9913
99.1%
1 87
 
0.9%
ValueCountFrequency (%)
0 9913
99.1%
1 87
 
0.9%
ValueCountFrequency (%)
1 87
 
0.9%
0 9913
99.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0609
Minimum0
Maximum1
Zeros9391
Zeros (%)93.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:22.213375image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2391587542
Coefficient of variation (CV)3.927073139
Kurtosis11.49155549
Mean0.0609
Median Absolute Deviation (MAD)0
Skewness3.672772415
Sum609
Variance0.05719690969
MonotonicityNot monotonic
2025-06-03T14:35:22.343945image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9391
93.9%
1 609
 
6.1%
ValueCountFrequency (%)
0 9391
93.9%
1 609
 
6.1%
ValueCountFrequency (%)
1 609
 
6.1%
0 9391
93.9%

project_prf_application_group_nan
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2482
Minimum0
Maximum1
Zeros7518
Zeros (%)75.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:22.471659image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4319900711
Coefficient of variation (CV)1.740491826
Kurtosis-0.6405704416
Mean0.2482
Median Absolute Deviation (MAD)0
Skewness1.166000734
Sum2482
Variance0.1866154215
MonotonicityNot monotonic
2025-06-03T14:35:22.599656image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 7518
75.2%
1 2482
 
24.8%
ValueCountFrequency (%)
0 7518
75.2%
1 2482
 
24.8%
ValueCountFrequency (%)
1 2482
 
24.8%
0 7518
75.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0484
Minimum0
Maximum1
Zeros9516
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:22.742662image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2146207031
Coefficient of variation (CV)4.434312048
Kurtosis15.72047781
Mean0.0484
Median Absolute Deviation (MAD)0
Skewness4.209196331
Sum484
Variance0.0460620462
MonotonicityNot monotonic
2025-06-03T14:35:22.874224image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9516
95.2%
1 484
 
4.8%
ValueCountFrequency (%)
0 9516
95.2%
1 484
 
4.8%
ValueCountFrequency (%)
1 484
 
4.8%
0 9516
95.2%
Distinct2
Distinct (%)< 0.1%
Missing190
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean0.009072375127
Minimum0
Maximum1
Zeros9721
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:23.011800image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09482079756
Coefficient of variation (CV)10.45159578
Kurtosis105.2881421
Mean0.009072375127
Median Absolute Deviation (MAD)0
Skewness10.35696272
Sum89
Variance0.008990983649
MonotonicityNot monotonic
2025-06-03T14:35:23.138679image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9721
97.2%
1 89
 
0.9%
(Missing) 190
 
1.9%
ValueCountFrequency (%)
0 9721
97.2%
1 89
 
0.9%
ValueCountFrequency (%)
1 89
 
0.9%
0 9721
97.2%

tech_tf_clientserver_description_client_server
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing167
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean0.01627173803
Minimum0
Maximum1
Zeros9673
Zeros (%)96.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:23.265487image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1265250829
Coefficient of variation (CV)7.775757129
Kurtosis56.50212779
Mean0.01627173803
Median Absolute Deviation (MAD)0
Skewness7.647917069
Sum160
Variance0.01600859661
MonotonicityNot monotonic
2025-06-03T14:35:23.395405image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9673
96.7%
1 160
 
1.6%
(Missing) 167
 
1.7%
ValueCountFrequency (%)
0 9673
96.7%
1 160
 
1.6%
ValueCountFrequency (%)
1 160
 
1.6%
0 9673
96.7%

tech_tf_clientserver_description_client_presentation
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing189
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean0.0002038528183
Minimum0
Maximum1
Zeros9809
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:23.546192image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01427697581
Coefficient of variation (CV)70.03570482
Kurtosis4902.999184
Mean0.0002038528183
Median Absolute Deviation (MAD)0
Skewness70.02856342
Sum2
Variance0.0002038320382
MonotonicityNot monotonic
2025-06-03T14:35:23.684832image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9809
98.1%
1 2
 
< 0.1%
(Missing) 189
 
1.9%
ValueCountFrequency (%)
0 9809
98.1%
1 2
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0 9809
98.1%

tech_tf_clientserver_description_client_presentation_processing
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing227
Missing (%)2.3%
Infinite0
Infinite (%)0.0%
Mean0.001330195436
Minimum0
Maximum1
Zeros9760
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:23.822487image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03644944387
Coefficient of variation (CV)27.40157038
Kurtosis747.1533757
Mean0.001330195436
Median Absolute Deviation (MAD)0
Skewness27.36787303
Sum13
Variance0.001328561959
MonotonicityNot monotonic
2025-06-03T14:35:23.942424image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9760
97.6%
1 13
 
0.1%
(Missing) 227
 
2.3%
ValueCountFrequency (%)
0 9760
97.6%
1 13
 
0.1%
ValueCountFrequency (%)
1 13
 
0.1%
0 9760
97.6%

tech_tf_clientserver_description_client_server_architecture
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing192
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean0.00234502447
Minimum0
Maximum1
Zeros9785
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:24.085513image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04837110591
Coefficient of variation (CV)20.62712203
Kurtosis421.6526676
Mean0.00234502447
Median Absolute Deviation (MAD)0
Skewness20.5807358
Sum23
Variance0.002339763887
MonotonicityNot monotonic
2025-06-03T14:35:24.225784image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9785
97.9%
1 23
 
0.2%
(Missing) 192
 
1.9%
ValueCountFrequency (%)
0 9785
97.9%
1 23
 
0.2%
ValueCountFrequency (%)
1 23
 
0.2%
0 9785
97.9%

tech_tf_clientserver_description_client_server_architecture_p2p
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing190
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean0.0001019367992
Minimum0
Maximum1
Zeros9809
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:24.356921image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01009637555
Coefficient of variation (CV)99.04544412
Kurtosis9810
Mean0.0001019367992
Median Absolute Deviation (MAD)0
Skewness99.04544412
Sum1
Variance0.0001019367992
MonotonicityNot monotonic
2025-06-03T14:35:24.490184image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9809
98.1%
1 1
 
< 0.1%
(Missing) 190
 
1.9%
ValueCountFrequency (%)
0 9809
98.1%
1 1
 
< 0.1%
ValueCountFrequency (%)
1 1
 
< 0.1%
0 9809
98.1%

tech_tf_clientserver_description_nan
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing166
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean0.9630872483
Minimum0
Maximum1
Zeros363
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:24.617960image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1885571951
Coefficient of variation (CV)0.195784126
Kurtosis22.14110251
Mean0.9630872483
Median Absolute Deviation (MAD)0
Skewness-4.91290134
Sum9471
Variance0.03555381584
MonotonicityNot monotonic
2025-06-03T14:35:24.742949image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 9471
94.7%
0 363
 
3.6%
(Missing) 166
 
1.7%
ValueCountFrequency (%)
0 363
 
3.6%
1 9471
94.7%
ValueCountFrequency (%)
1 9471
94.7%
0 363
 
3.6%

tech_tf_clientserver_description_server_processing
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing166
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean0.0003050640635
Minimum0
Maximum1
Zeros9831
Zeros (%)98.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:24.877943image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01746430687
Coefficient of variation (CV)57.24799792
Kurtosis3274.66565
Mean0.0003050640635
Median Absolute Deviation (MAD)0
Skewness57.23634912
Sum3
Variance0.0003050020144
MonotonicityNot monotonic
2025-06-03T14:35:25.010505image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9831
98.3%
1 3
 
< 0.1%
(Missing) 166
 
1.7%
ValueCountFrequency (%)
0 9831
98.3%
1 3
 
< 0.1%
ValueCountFrequency (%)
1 3
 
< 0.1%
0 9831
98.3%

tech_tf_clientserver_description_stand_alone
Real number (ℝ)

Missing  Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing207
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean0.002042275094
Minimum0
Maximum1
Zeros9773
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:25.140471image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04514767266
Coefficient of variation (CV)22.10655792
Kurtosis484.9001986
Mean0.002042275094
Median Absolute Deviation (MAD)0
Skewness22.06357108
Sum20
Variance0.002038312347
MonotonicityNot monotonic
2025-06-03T14:35:25.276878image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9773
97.7%
1 20
 
0.2%
(Missing) 207
 
2.1%
ValueCountFrequency (%)
0 9773
97.7%
1 20
 
0.2%
ValueCountFrequency (%)
1 20
 
0.2%
0 9773
97.7%

tech_tf_clientserver_description_web
Real number (ℝ)

Missing  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing189
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean0.006523290184
Minimum0
Maximum1
Zeros9747
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:25.415547image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08050712698
Coefficient of variation (CV)12.34149098
Kurtosis148.3796609
Mean0.006523290184
Median Absolute Deviation (MAD)0
Skewness12.26170515
Sum64
Variance0.006481397495
MonotonicityNot monotonic
2025-06-03T14:35:25.557462image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9747
97.5%
1 64
 
0.6%
(Missing) 189
 
1.9%
ValueCountFrequency (%)
0 9747
97.5%
1 64
 
0.6%
ValueCountFrequency (%)
1 64
 
0.6%
0 9747
97.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8743 
True
1257 
ValueCountFrequency (%)
False 8743
87.4%
True 1257
 
12.6%
2025-06-03T14:35:25.693760image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8283 
False
1717 
ValueCountFrequency (%)
True 8283
82.8%
False 1717
 
17.2%
2025-06-03T14:35:25.802503image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9687 
True
 
313
ValueCountFrequency (%)
False 9687
96.9%
True 313
 
3.1%
2025-06-03T14:35:25.913646image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9734 
True
 
266
ValueCountFrequency (%)
False 9734
97.3%
True 266
 
2.7%
2025-06-03T14:35:26.008243image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
7586 
False
2414 
ValueCountFrequency (%)
True 7586
75.9%
False 2414
 
24.1%
2025-06-03T14:35:26.135982image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7612 
True
2388 
ValueCountFrequency (%)
False 7612
76.1%
True 2388
 
23.9%
2025-06-03T14:35:26.264073image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9992 
True
 
8
ValueCountFrequency (%)
False 9992
99.9%
True 8
 
0.1%
2025-06-03T14:35:26.395365image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2025-06-03T14:35:26.506202image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:26.626219image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9915 
True
 
85
ValueCountFrequency (%)
False 9915
99.2%
True 85
 
0.9%
2025-06-03T14:35:26.726639image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8344 
True
1656 
ValueCountFrequency (%)
False 8344
83.4%
True 1656
 
16.6%
2025-06-03T14:35:26.837336image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9245 
True
 
755
ValueCountFrequency (%)
False 9245
92.5%
True 755
 
7.5%
2025-06-03T14:35:26.942228image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
6546 
True
3454 
ValueCountFrequency (%)
False 6546
65.5%
True 3454
34.5%
2025-06-03T14:35:27.043232image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7223 
True
2777 
ValueCountFrequency (%)
False 7223
72.2%
True 2777
 
27.8%
2025-06-03T14:35:27.160850image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8697 
True
1303 
ValueCountFrequency (%)
False 8697
87.0%
True 1303
 
13.0%
2025-06-03T14:35:27.459586image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9961 
True
 
39
ValueCountFrequency (%)
False 9961
99.6%
True 39
 
0.4%
2025-06-03T14:35:27.571650image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_2gl
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9992 
True
 
8
ValueCountFrequency (%)
False 9992
99.9%
True 8
 
0.1%
2025-06-03T14:35:27.708606image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
5253 
False
4747 
ValueCountFrequency (%)
True 5253
52.5%
False 4747
47.5%
2025-06-03T14:35:27.834700image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7839 
True
2161 
ValueCountFrequency (%)
False 7839
78.4%
True 2161
 
21.6%
2025-06-03T14:35:27.959751image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_5gl
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9980 
True
 
20
ValueCountFrequency (%)
False 9980
99.8%
True 20
 
0.2%
2025-06-03T14:35:28.071976image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_language_type_apg
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9785 
True
 
215
ValueCountFrequency (%)
False 9785
97.9%
True 215
 
2.1%
2025-06-03T14:35:28.199665image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7842 
True
2158 
ValueCountFrequency (%)
False 7842
78.4%
True 2158
 
21.6%
2025-06-03T14:35:28.316895image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_l
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9682 
True
 
318
ValueCountFrequency (%)
False 9682
96.8%
True 318
 
3.2%
2025-06-03T14:35:28.427548image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
6714 
True
3286 
ValueCountFrequency (%)
False 6714
67.1%
True 3286
32.9%
2025-06-03T14:35:28.543933image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8706 
True
1294 
ValueCountFrequency (%)
False 8706
87.1%
True 1294
 
12.9%
2025-06-03T14:35:28.671921image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9629 
True
 
371
ValueCountFrequency (%)
False 9629
96.3%
True 371
 
3.7%
2025-06-03T14:35:28.786047image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
6938 
True
3062 
ValueCountFrequency (%)
False 6938
69.4%
True 3062
30.6%
2025-06-03T14:35:28.897252image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_xl
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9967 
True
 
33
ValueCountFrequency (%)
False 9967
99.7%
True 33
 
0.3%
2025-06-03T14:35:29.010814image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

project_prf_relative_size_xs
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9036 
True
964 
ValueCountFrequency (%)
False 9036
90.4%
True 964
 
9.6%
2025-06-03T14:35:29.124178image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9995 
True
 
5
ValueCountFrequency (%)
False 9995
> 99.9%
True 5
 
0.1%
2025-06-03T14:35:29.243303image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9440 
True
 
560
ValueCountFrequency (%)
False 9440
94.4%
True 560
 
5.6%
2025-06-03T14:35:29.355530image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9987 
True
 
13
ValueCountFrequency (%)
False 9987
99.9%
True 13
 
0.1%
2025-06-03T14:35:29.457855image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8621 
False
1379 
ValueCountFrequency (%)
True 8621
86.2%
False 1379
 
13.8%
2025-06-03T14:35:29.568008image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9440 
True
 
560
ValueCountFrequency (%)
False 9440
94.4%
True 560
 
5.6%
2025-06-03T14:35:29.680455image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9076 
True
924 
ValueCountFrequency (%)
False 9076
90.8%
True 924
 
9.2%
2025-06-03T14:35:29.792432image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
7749 
False
2251 
ValueCountFrequency (%)
True 7749
77.5%
False 2251
 
22.5%
2025-06-03T14:35:29.902370image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7727 
True
2273 
ValueCountFrequency (%)
False 7727
77.3%
True 2273
 
22.7%
2025-06-03T14:35:30.007945image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8088 
True
1912 
ValueCountFrequency (%)
False 8088
80.9%
True 1912
 
19.1%
2025-06-03T14:35:30.120489image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8772 
True
1228 
ValueCountFrequency (%)
False 8772
87.7%
True 1228
 
12.3%
2025-06-03T14:35:30.229215image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9931 
True
 
69
ValueCountFrequency (%)
False 9931
99.3%
True 69
 
0.7%
2025-06-03T14:35:30.344282image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9541 
True
 
459
ValueCountFrequency (%)
False 9541
95.4%
True 459
 
4.6%
2025-06-03T14:35:30.442365image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
5267 
True
4733 
ValueCountFrequency (%)
False 5267
52.7%
True 4733
47.3%
2025-06-03T14:35:30.567097image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9974 
True
 
26
ValueCountFrequency (%)
False 9974
99.7%
True 26
 
0.3%
2025-06-03T14:35:30.698488image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8388 
True
1612 
ValueCountFrequency (%)
False 8388
83.9%
True 1612
 
16.1%
2025-06-03T14:35:30.822736image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9962 
True
 
38
ValueCountFrequency (%)
False 9962
99.6%
True 38
 
0.4%
2025-06-03T14:35:30.949605image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
7022 
False
2978 
ValueCountFrequency (%)
True 7022
70.2%
False 2978
29.8%
2025-06-03T14:35:31.061048image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_client_server_no
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9289 
True
 
711
ValueCountFrequency (%)
False 9289
92.9%
True 711
 
7.1%
2025-06-03T14:35:31.180285image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
7676 
True
2324 
ValueCountFrequency (%)
False 7676
76.8%
True 2324
 
23.2%
2025-06-03T14:35:31.285669image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9988 
True
 
12
ValueCountFrequency (%)
False 9988
99.9%
True 12
 
0.1%
2025-06-03T14:35:31.410847image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9218 
True
 
782
ValueCountFrequency (%)
False 9218
92.2%
True 782
 
7.8%
2025-06-03T14:35:31.504647image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9989 
True
 
11
ValueCountFrequency (%)
False 9989
99.9%
True 11
 
0.1%
2025-06-03T14:35:31.621276image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9806 
True
 
194
ValueCountFrequency (%)
False 9806
98.1%
True 194
 
1.9%
2025-06-03T14:35:31.725847image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9939 
True
 
61
ValueCountFrequency (%)
False 9939
99.4%
True 61
 
0.6%
2025-06-03T14:35:31.833923image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8846 
False
1154 
ValueCountFrequency (%)
True 8846
88.5%
False 1154
 
11.5%
2025-06-03T14:35:31.942160image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9911 
True
 
89
ValueCountFrequency (%)
False 9911
99.1%
True 89
 
0.9%
2025-06-03T14:35:32.049384image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_type_of_server_unix
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9978 
True
 
22
ValueCountFrequency (%)
False 9978
99.8%
True 22
 
0.2%
2025-06-03T14:35:32.154648image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2025-06-03T14:35:32.254459image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
8158 
False
1842 
ValueCountFrequency (%)
True 8158
81.6%
False 1842
 
18.4%
2025-06-03T14:35:32.368585image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8168 
True
1832 
ValueCountFrequency (%)
False 8168
81.7%
True 1832
 
18.3%
2025-06-03T14:35:32.475400image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
5712 
False
4288 
ValueCountFrequency (%)
True 5712
57.1%
False 4288
42.9%
2025-06-03T14:35:32.582577image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_dbms_used_no
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9950 
True
 
50
ValueCountFrequency (%)
False 9950
99.5%
True 50
 
0.5%
2025-06-03T14:35:32.693850image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
5765 
True
4235 
ValueCountFrequency (%)
False 5765
57.6%
True 4235
42.4%
2025-06-03T14:35:32.800789image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2025-06-03T14:35:32.909024image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9994 
True
 
6
ValueCountFrequency (%)
False 9994
99.9%
True 6
 
0.1%
2025-06-03T14:35:33.010543image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:33.129634image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
9898 
False
 
102
ValueCountFrequency (%)
True 9898
99.0%
False 102
 
1.0%
2025-06-03T14:35:33.264259image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9999 
True
 
1
ValueCountFrequency (%)
False 9999
> 99.9%
True 1
 
< 0.1%
2025-06-03T14:35:33.401463image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9939 
True
 
61
ValueCountFrequency (%)
False 9939
99.4%
True 61
 
0.6%
2025-06-03T14:35:33.601615image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
True
7941 
False
2059 
ValueCountFrequency (%)
True 7941
79.4%
False 2059
 
20.6%
2025-06-03T14:35:33.772322image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
8016 
True
1984 
ValueCountFrequency (%)
False 8016
80.2%
True 1984
 
19.8%
2025-06-03T14:35:33.879694image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9997 
True
 
3
ValueCountFrequency (%)
False 9997
> 99.9%
True 3
 
< 0.1%
2025-06-03T14:35:34.030425image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
9998 
True
 
2
ValueCountFrequency (%)
False 9998
> 99.9%
True 2
 
< 0.1%
2025-06-03T14:35:34.201645image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1416
Minimum0
Maximum1
Zeros8584
Zeros (%)85.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:34.367572image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3486568459
Coefficient of variation (CV)2.462265861
Kurtosis2.228819148
Mean0.1416
Median Absolute Deviation (MAD)0
Skewness2.056300908
Sum1416
Variance0.1215615962
MonotonicityNot monotonic
2025-06-03T14:35:34.520590image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8584
85.8%
1 1416
 
14.2%
ValueCountFrequency (%)
0 8584
85.8%
1 1416
 
14.2%
ValueCountFrequency (%)
1 1416
 
14.2%
0 8584
85.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.142
Minimum0
Maximum1
Zeros8580
Zeros (%)85.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:34.658388image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3490675935
Coefficient of variation (CV)2.458222489
Kurtosis2.209459202
Mean0.142
Median Absolute Deviation (MAD)0
Skewness2.051588982
Sum1420
Variance0.1218481848
MonotonicityNot monotonic
2025-06-03T14:35:34.789042image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8580
85.8%
1 1420
 
14.2%
ValueCountFrequency (%)
0 8580
85.8%
1 1420
 
14.2%
ValueCountFrequency (%)
1 1420
 
14.2%
0 8580
85.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1339
Minimum0
Maximum1
Zeros8661
Zeros (%)86.6%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:34.916178image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3405618714
Coefficient of variation (CV)2.543404566
Kurtosis2.624773124
Mean0.1339
Median Absolute Deviation (MAD)0
Skewness2.150406522
Sum1339
Variance0.1159823882
MonotonicityNot monotonic
2025-06-03T14:35:35.285642image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8661
86.6%
1 1339
 
13.4%
ValueCountFrequency (%)
0 8661
86.6%
1 1339
 
13.4%
ValueCountFrequency (%)
1 1339
 
13.4%
0 8661
86.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1385
Minimum0
Maximum1
Zeros8615
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:35.444884image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3454412873
Coefficient of variation (CV)2.494160919
Kurtosis2.382773872
Mean0.1385
Median Absolute Deviation (MAD)0
Skewness2.093393742
Sum1385
Variance0.119329683
MonotonicityNot monotonic
2025-06-03T14:35:35.573936image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8615
86.2%
1 1385
 
13.9%
ValueCountFrequency (%)
0 8615
86.2%
1 1385
 
13.9%
ValueCountFrequency (%)
1 1385
 
13.9%
0 8615
86.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1046
Minimum0
Maximum1
Zeros8954
Zeros (%)89.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:35.703319image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.306052621
Coefficient of variation (CV)2.925933279
Kurtosis4.679988351
Mean0.1046
Median Absolute Deviation (MAD)0
Skewness2.58438627
Sum1046
Variance0.09366820682
MonotonicityNot monotonic
2025-06-03T14:35:35.845766image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8954
89.5%
1 1046
 
10.5%
ValueCountFrequency (%)
0 8954
89.5%
1 1046
 
10.5%
ValueCountFrequency (%)
1 1046
 
10.5%
0 8954
89.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0966
Minimum0
Maximum1
Zeros9034
Zeros (%)90.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:36.025023image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2954270937
Coefficient of variation (CV)3.058251488
Kurtosis5.462226923
Mean0.0966
Median Absolute Deviation (MAD)0
Skewness2.731507737
Sum966
Variance0.08727716772
MonotonicityNot monotonic
2025-06-03T14:35:36.160891image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9034
90.3%
1 966
 
9.7%
ValueCountFrequency (%)
0 9034
90.3%
1 966
 
9.7%
ValueCountFrequency (%)
1 966
 
9.7%
0 9034
90.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0761
Minimum0
Maximum1
Zeros9239
Zeros (%)92.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:36.293631image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2651713061
Coefficient of variation (CV)3.48451125
Kurtosis8.227685897
Mean0.0761
Median Absolute Deviation (MAD)0
Skewness3.197818069
Sum761
Variance0.07031582158
MonotonicityNot monotonic
2025-06-03T14:35:36.410862image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9239
92.4%
1 761
 
7.6%
ValueCountFrequency (%)
0 9239
92.4%
1 761
 
7.6%
ValueCountFrequency (%)
1 761
 
7.6%
0 9239
92.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0564
Minimum0
Maximum1
Zeros9436
Zeros (%)94.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:36.553503image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2307040581
Coefficient of variation (CV)4.090497485
Kurtosis12.79726522
Mean0.0564
Median Absolute Deviation (MAD)0
Skewness3.846388671
Sum564
Variance0.05322436244
MonotonicityNot monotonic
2025-06-03T14:35:36.684552image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9436
94.4%
1 564
 
5.6%
ValueCountFrequency (%)
0 9436
94.4%
1 564
 
5.6%
ValueCountFrequency (%)
1 564
 
5.6%
0 9436
94.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0233
Minimum0
Maximum1
Zeros9767
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:36.813696image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1508621422
Coefficient of variation (CV)6.47477005
Kurtosis37.961889
Mean0.0233
Median Absolute Deviation (MAD)0
Skewness6.320941122
Sum233
Variance0.02275938594
MonotonicityNot monotonic
2025-06-03T14:35:36.946027image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%
ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%
ValueCountFrequency (%)
1 233
 
2.3%
0 9767
97.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0205
Minimum0
Maximum1
Zeros9795
Zeros (%)98.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:37.076966image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1417101202
Coefficient of variation (CV)6.912688792
Kurtosis43.82392569
Mean0.0205
Median Absolute Deviation (MAD)0
Skewness6.768689751
Sum205
Variance0.02008175818
MonotonicityNot monotonic
2025-06-03T14:35:37.214362image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9795
98.0%
1 205
 
2.1%
ValueCountFrequency (%)
0 9795
98.0%
1 205
 
2.1%
ValueCountFrequency (%)
1 205
 
2.1%
0 9795
98.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0176
Minimum0
Maximum1
Zeros9824
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:37.346544image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1314989323
Coefficient of variation (CV)7.471530245
Kurtosis51.86262475
Mean0.0176
Median Absolute Deviation (MAD)0
Skewness7.338409382
Sum176
Variance0.0172919692
MonotonicityNot monotonic
2025-06-03T14:35:37.473259image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9824
98.2%
1 176
 
1.8%
ValueCountFrequency (%)
0 9824
98.2%
1 176
 
1.8%
ValueCountFrequency (%)
1 176
 
1.8%
0 9824
98.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0194
Minimum0
Maximum1
Zeros9806
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:37.606812image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.137933109
Coefficient of variation (CV)7.109954071
Kurtosis46.59006727
Mean0.0194
Median Absolute Deviation (MAD)0
Skewness6.969989189
Sum194
Variance0.01902554255
MonotonicityNot monotonic
2025-06-03T14:35:37.742085image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9806
98.1%
1 194
 
1.9%
ValueCountFrequency (%)
0 9806
98.1%
1 194
 
1.9%
ValueCountFrequency (%)
1 194
 
1.9%
0 9806
98.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0174
Minimum0
Maximum1
Zeros9826
Zeros (%)98.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:37.879352image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1307629531
Coefficient of variation (CV)7.515112245
Kurtosis52.51582667
Mean0.0174
Median Absolute Deviation (MAD)0
Skewness7.382772077
Sum174
Variance0.01709894989
MonotonicityNot monotonic
2025-06-03T14:35:38.013126image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9826
98.3%
1 174
 
1.7%
ValueCountFrequency (%)
0 9826
98.3%
1 174
 
1.7%
ValueCountFrequency (%)
1 174
 
1.7%
0 9826
98.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.012
Minimum0
Maximum1
Zeros9880
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:38.161034image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1088907054
Coefficient of variation (CV)9.074225448
Kurtosis78.38526617
Mean0.012
Median Absolute Deviation (MAD)0
Skewness8.964908764
Sum120
Variance0.01185718572
MonotonicityNot monotonic
2025-06-03T14:35:38.297663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9880
98.8%
1 120
 
1.2%
ValueCountFrequency (%)
0 9880
98.8%
1 120
 
1.2%
ValueCountFrequency (%)
1 120
 
1.2%
0 9880
98.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0127
Minimum0
Maximum1
Zeros9873
Zeros (%)98.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:38.426751image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1119819807
Coefficient of variation (CV)8.817478793
Kurtosis73.79051088
Mean0.0127
Median Absolute Deviation (MAD)0
Skewness8.704926927
Sum127
Variance0.012539964
MonotonicityNot monotonic
2025-06-03T14:35:38.562663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9873
98.7%
1 127
 
1.3%
ValueCountFrequency (%)
0 9873
98.7%
1 127
 
1.3%
ValueCountFrequency (%)
1 127
 
1.3%
0 9873
98.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0121
Minimum0
Maximum1
Zeros9879
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:38.695108image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1093379416
Coefficient of variation (CV)9.036193523
Kurtosis77.69631896
Mean0.0121
Median Absolute Deviation (MAD)0
Skewness8.926409118
Sum121
Variance0.01195478548
MonotonicityNot monotonic
2025-06-03T14:35:38.822412image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9879
98.8%
1 121
 
1.2%
ValueCountFrequency (%)
0 9879
98.8%
1 121
 
1.2%
ValueCountFrequency (%)
1 121
 
1.2%
0 9879
98.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0116
Minimum0
Maximum1
Zeros9884
Zeros (%)98.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:38.965665image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1070821491
Coefficient of variation (CV)9.231219751
Kurtosis81.25985687
Mean0.0116
Median Absolute Deviation (MAD)0
Skewness9.123793342
Sum116
Variance0.01146658666
MonotonicityNot monotonic
2025-06-03T14:35:39.108309image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9884
98.8%
1 116
 
1.2%
ValueCountFrequency (%)
0 9884
98.8%
1 116
 
1.2%
ValueCountFrequency (%)
1 116
 
1.2%
0 9884
98.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.009
Minimum0
Maximum1
Zeros9910
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:39.242177image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09444517981
Coefficient of variation (CV)10.49390887
Kurtosis106.1738723
Mean0.009
Median Absolute Deviation (MAD)0
Skewness10.39964603
Sum90
Variance0.008919891989
MonotonicityNot monotonic
2025-06-03T14:35:39.375763image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9910
99.1%
1 90
 
0.9%
ValueCountFrequency (%)
0 9910
99.1%
1 90
 
0.9%
ValueCountFrequency (%)
1 90
 
0.9%
0 9910
99.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0101
Minimum0
Maximum1
Zeros9899
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:39.504669image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09999494937
Coefficient of variation (CV)9.900490036
Kurtosis94.06773126
Mean0.0101
Median Absolute Deviation (MAD)0
Skewness9.800454977
Sum101
Variance0.009998989899
MonotonicityNot monotonic
2025-06-03T14:35:39.634481image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9899
99.0%
1 101
 
1.0%
ValueCountFrequency (%)
0 9899
99.0%
1 101
 
1.0%
ValueCountFrequency (%)
1 101
 
1.0%
0 9899
99.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0088
Minimum0
Maximum1
Zeros9912
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:39.768126image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09339931661
Coefficient of variation (CV)10.61355871
Kurtosis108.7001842
Mean0.0088
Median Absolute Deviation (MAD)0
Skewness10.52038232
Sum88
Variance0.008723432343
MonotonicityNot monotonic
2025-06-03T14:35:39.896543image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%
ValueCountFrequency (%)
0 9912
99.1%
1 88
 
0.9%
ValueCountFrequency (%)
1 88
 
0.9%
0 9912
99.1%

external_eef_organisation_type_other
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0505
Minimum0
Maximum1
Zeros9495
Zeros (%)95.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:40.036039image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2189852631
Coefficient of variation (CV)4.336341844
Kurtosis14.86319658
Mean0.0505
Median Absolute Deviation (MAD)0
Skewness4.106120308
Sum505
Variance0.04795454545
MonotonicityNot monotonic
2025-06-03T14:35:40.165940image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9495
95.0%
1 505
 
5.1%
ValueCountFrequency (%)
0 9495
95.0%
1 505
 
5.1%
ValueCountFrequency (%)
1 505
 
5.1%
0 9495
95.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1608
Minimum0
Maximum1
Zeros8392
Zeros (%)83.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:40.294862image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3673647448
Coefficient of variation (CV)2.284606622
Kurtosis1.411822283
Mean0.1608
Median Absolute Deviation (MAD)0
Skewness1.847035451
Sum1608
Variance0.1349568557
MonotonicityNot monotonic
2025-06-03T14:35:40.427077image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8392
83.9%
1 1608
 
16.1%
ValueCountFrequency (%)
0 8392
83.9%
1 1608
 
16.1%
ValueCountFrequency (%)
1 1608
 
16.1%
0 8392
83.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1422
Minimum0
Maximum1
Zeros8578
Zeros (%)85.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:40.553556image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3492726144
Coefficient of variation (CV)2.456206852
Kurtosis2.199821409
Mean0.1422
Median Absolute Deviation (MAD)0
Skewness2.049239245
Sum1422
Variance0.1219913591
MonotonicityNot monotonic
2025-06-03T14:35:40.684609image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8578
85.8%
1 1422
 
14.2%
ValueCountFrequency (%)
0 8578
85.8%
1 1422
 
14.2%
ValueCountFrequency (%)
1 1422
 
14.2%
0 8578
85.8%

project_prf_application_type_top_nan
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1081
Minimum0
Maximum1
Zeros8919
Zeros (%)89.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:40.813793image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3105221931
Coefficient of variation (CV)2.872545727
Kurtosis4.374682706
Mean0.1081
Median Absolute Deviation (MAD)0
Skewness2.524640135
Sum1081
Variance0.0964240324
MonotonicityNot monotonic
2025-06-03T14:35:40.941972image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 8919
89.2%
1 1081
 
10.8%
ValueCountFrequency (%)
0 8919
89.2%
1 1081
 
10.8%
ValueCountFrequency (%)
1 1081
 
10.8%
0 8919
89.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0703
Minimum0
Maximum1
Zeros9297
Zeros (%)93.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:41.070854image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2556647149
Coefficient of variation (CV)3.636766926
Kurtosis9.305618955
Mean0.0703
Median Absolute Deviation (MAD)0
Skewness3.362106166
Sum703
Variance0.06536444644
MonotonicityNot monotonic
2025-06-03T14:35:41.200179image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9297
93.0%
1 703
 
7.0%
ValueCountFrequency (%)
0 9297
93.0%
1 703
 
7.0%
ValueCountFrequency (%)
1 703
 
7.0%
0 9297
93.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0548
Minimum0
Maximum1
Zeros9452
Zeros (%)94.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:41.328425image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2276008353
Coefficient of variation (CV)4.153299914
Kurtosis13.31340804
Mean0.0548
Median Absolute Deviation (MAD)0
Skewness3.91289476
Sum548
Variance0.05180214021
MonotonicityNot monotonic
2025-06-03T14:35:41.461094image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9452
94.5%
1 548
 
5.5%
ValueCountFrequency (%)
0 9452
94.5%
1 548
 
5.5%
ValueCountFrequency (%)
1 548
 
5.5%
0 9452
94.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0449
Minimum0
Maximum1
Zeros9551
Zeros (%)95.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:41.590073image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2070948547
Coefficient of variation (CV)4.612357565
Kurtosis17.32798843
Mean0.0449
Median Absolute Deviation (MAD)0
Skewness4.395966659
Sum449
Variance0.04288827883
MonotonicityNot monotonic
2025-06-03T14:35:41.723378image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9551
95.5%
1 449
 
4.5%
ValueCountFrequency (%)
0 9551
95.5%
1 449
 
4.5%
ValueCountFrequency (%)
1 449
 
4.5%
0 9551
95.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0356
Minimum0
Maximum1
Zeros9644
Zeros (%)96.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:41.857702image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1852999558
Coefficient of variation (CV)5.205054937
Kurtosis23.13896959
Mean0.0356
Median Absolute Deviation (MAD)0
Skewness5.013416184
Sum356
Variance0.03433607361
MonotonicityNot monotonic
2025-06-03T14:35:41.990460image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9644
96.4%
1 356
 
3.6%
ValueCountFrequency (%)
0 9644
96.4%
1 356
 
3.6%
ValueCountFrequency (%)
1 356
 
3.6%
0 9644
96.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0315
Minimum0
Maximum1
Zeros9685
Zeros (%)96.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:42.132465image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1746734126
Coefficient of variation (CV)5.545187703
Kurtosis26.79255061
Mean0.0315
Median Absolute Deviation (MAD)0
Skewness5.365369711
Sum315
Variance0.03051080108
MonotonicityNot monotonic
2025-06-03T14:35:42.274500image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9685
96.9%
1 315
 
3.1%
ValueCountFrequency (%)
0 9685
96.9%
1 315
 
3.1%
ValueCountFrequency (%)
1 315
 
3.1%
0 9685
96.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0254
Minimum0
Maximum1
Zeros9746
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:42.430439image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1573445764
Coefficient of variation (CV)6.194668363
Kurtosis34.41394522
Mean0.0254
Median Absolute Deviation (MAD)0
Skewness6.03382652
Sum254
Variance0.02475731573
MonotonicityNot monotonic
2025-06-03T14:35:42.580710image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9746
97.5%
1 254
 
2.5%
ValueCountFrequency (%)
0 9746
97.5%
1 254
 
2.5%
ValueCountFrequency (%)
1 254
 
2.5%
0 9746
97.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0222
Minimum0
Maximum1
Zeros9778
Zeros (%)97.8%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:42.718959image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1473408665
Coefficient of variation (CV)6.636975967
Kurtosis40.0883904
Mean0.0222
Median Absolute Deviation (MAD)0
Skewness6.486938628
Sum222
Variance0.02170933093
MonotonicityNot monotonic
2025-06-03T14:35:42.852274image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9778
97.8%
1 222
 
2.2%
ValueCountFrequency (%)
0 9778
97.8%
1 222
 
2.2%
ValueCountFrequency (%)
1 222
 
2.2%
0 9778
97.8%
Distinct2
Distinct (%)< 0.1%
Missing269
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean0.02106669407
Minimum0
Maximum1
Zeros9526
Zeros (%)95.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:42.980194image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.143614094
Coefficient of variation (CV)6.817115846
Kurtosis42.51226984
Mean0.02106669407
Median Absolute Deviation (MAD)0
Skewness6.671096791
Sum205
Variance0.02062500799
MonotonicityNot monotonic
2025-06-03T14:35:43.123895image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9526
95.3%
1 205
 
2.1%
(Missing) 269
 
2.7%
ValueCountFrequency (%)
0 9526
95.3%
1 205
 
2.1%
ValueCountFrequency (%)
1 205
 
2.1%
0 9526
95.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0233
Minimum0
Maximum1
Zeros9767
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:43.264893image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1508621422
Coefficient of variation (CV)6.47477005
Kurtosis37.961889
Mean0.0233
Median Absolute Deviation (MAD)0
Skewness6.320941122
Sum233
Variance0.02275938594
MonotonicityNot monotonic
2025-06-03T14:35:43.411091image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%
ValueCountFrequency (%)
0 9767
97.7%
1 233
 
2.3%
ValueCountFrequency (%)
1 233
 
2.3%
0 9767
97.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0164
Minimum0
Maximum1
Zeros9836
Zeros (%)98.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:43.560319image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1270143821
Coefficient of variation (CV)7.744779398
Kurtosis56.02088966
Mean0.0164
Median Absolute Deviation (MAD)0
Skewness7.616408965
Sum164
Variance0.01613265327
MonotonicityNot monotonic
2025-06-03T14:35:43.711744image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9836
98.4%
1 164
 
1.6%
ValueCountFrequency (%)
0 9836
98.4%
1 164
 
1.6%
ValueCountFrequency (%)
1 164
 
1.6%
0 9836
98.4%
Distinct2
Distinct (%)< 0.1%
Missing208
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean0.01613562092
Minimum0
Maximum1
Zeros9634
Zeros (%)96.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:43.865378image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1260035082
Coefficient of variation (CV)7.809027543
Kurtosis57.02080833
Mean0.01613562092
Median Absolute Deviation (MAD)0
Skewness7.681742118
Sum158
Variance0.01587688407
MonotonicityNot monotonic
2025-06-03T14:35:44.020387image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9634
96.3%
1 158
 
1.6%
(Missing) 208
 
2.1%
ValueCountFrequency (%)
0 9634
96.3%
1 158
 
1.6%
ValueCountFrequency (%)
1 158
 
1.6%
0 9634
96.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0143
Minimum0
Maximum1
Zeros9857
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:44.170219image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1187304497
Coefficient of variation (CV)8.302828652
Kurtosis64.97766161
Mean0.0143
Median Absolute Deviation (MAD)0
Skewness8.183194127
Sum143
Variance0.01409691969
MonotonicityNot monotonic
2025-06-03T14:35:44.325922image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9857
98.6%
1 143
 
1.4%
ValueCountFrequency (%)
0 9857
98.6%
1 143
 
1.4%
ValueCountFrequency (%)
1 143
 
1.4%
0 9857
98.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0159
Minimum0
Maximum1
Zeros9841
Zeros (%)98.4%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:44.467690image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1250949834
Coefficient of variation (CV)7.86760902
Kurtosis57.93880394
Mean0.0159
Median Absolute Deviation (MAD)0
Skewness7.741267094
Sum159
Variance0.01564875488
MonotonicityNot monotonic
2025-06-03T14:35:44.600575image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9841
98.4%
1 159
 
1.6%
ValueCountFrequency (%)
0 9841
98.4%
1 159
 
1.6%
ValueCountFrequency (%)
1 159
 
1.6%
0 9841
98.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0176
Minimum0
Maximum1
Zeros9824
Zeros (%)98.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:44.727118image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1314989323
Coefficient of variation (CV)7.471530245
Kurtosis51.86262475
Mean0.0176
Median Absolute Deviation (MAD)0
Skewness7.338409382
Sum176
Variance0.0172919692
MonotonicityNot monotonic
2025-06-03T14:35:44.853482image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9824
98.2%
1 176
 
1.8%
ValueCountFrequency (%)
0 9824
98.2%
1 176
 
1.8%
ValueCountFrequency (%)
1 176
 
1.8%
0 9824
98.2%
Distinct2
Distinct (%)< 0.1%
Missing215
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean0.01011752683
Minimum0
Maximum1
Zeros9686
Zeros (%)96.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:45.006806image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1000808978
Coefficient of variation (CV)9.891834192
Kurtosis93.8971912
Mean0.01011752683
Median Absolute Deviation (MAD)0
Skewness9.791731163
Sum99
Variance0.0100161861
MonotonicityNot monotonic
2025-06-03T14:35:45.137180image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9686
96.9%
1 99
 
1.0%
(Missing) 215
 
2.1%
ValueCountFrequency (%)
0 9686
96.9%
1 99
 
1.0%
ValueCountFrequency (%)
1 99
 
1.0%
0 9686
96.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0112
Minimum0
Maximum1
Zeros9888
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:45.296780image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1052409976
Coefficient of variation (CV)9.396517639
Kurtosis84.33980509
Mean0.0112
Median Absolute Deviation (MAD)0
Skewness9.291013786
Sum112
Variance0.01107566757
MonotonicityNot monotonic
2025-06-03T14:35:45.444241image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9888
98.9%
1 112
 
1.1%
ValueCountFrequency (%)
0 9888
98.9%
1 112
 
1.1%
ValueCountFrequency (%)
1 112
 
1.1%
0 9888
98.9%
Distinct2
Distinct (%)< 0.1%
Missing201
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean0.01020512297
Minimum0
Maximum1
Zeros9699
Zeros (%)97.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:45.584589image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1005087527
Coefficient of variation (CV)9.848852672
Kurtosis93.04839432
Mean0.01020512297
Median Absolute Deviation (MAD)0
Skewness9.748302568
Sum100
Variance0.01010200936
MonotonicityNot monotonic
2025-06-03T14:35:45.717727image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 9699
97.0%
1 100
 
1.0%
(Missing) 201
 
2.0%
ValueCountFrequency (%)
0 9699
97.0%
1 100
 
1.0%
ValueCountFrequency (%)
1 100
 
1.0%
0 9699
97.0%

project_prf_application_type_other
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2483
Minimum0
Maximum1
Zeros7517
Zeros (%)75.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:46.164608image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4320483498
Coefficient of variation (CV)1.740025573
Kurtosis-0.6420168512
Mean0.2483
Median Absolute Deviation (MAD)0
Skewness1.16538045
Sum2483
Variance0.1866657766
MonotonicityNot monotonic
2025-06-03T14:35:46.303396image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 7517
75.2%
1 2483
 
24.8%
ValueCountFrequency (%)
0 7517
75.2%
1 2483
 
24.8%
ValueCountFrequency (%)
1 2483
 
24.8%
0 7517
75.2%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:46.443060image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length40
Median length38
Mean length16.9316
Min length3

Characters and Unicode

Total characters169316
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMissing
2nd rowclient: presentation; server: processing
3rd rowclient: presentation; server: processing
4th rowMissing
5th rowMissing
ValueCountFrequency (%)
missing 3839
19.4%
client 3564
18.0%
presentation 3564
18.0%
processing 3564
18.0%
c/s 2597
13.1%
server 2373
12.0%
data 270
 
1.4%
2025-06-03T14:35:46.775921image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 23340
13.8%
e 19002
11.2%
i 18370
10.8%
n 18095
10.7%
r 11874
 
7.0%
t 10962
 
6.5%
9771
 
5.8%
c 9725
 
5.7%
g 7403
 
4.4%
o 7128
 
4.2%
Other values (10) 33646
19.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 169316
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 23340
13.8%
e 19002
11.2%
i 18370
10.8%
n 18095
10.7%
r 11874
 
7.0%
t 10962
 
6.5%
9771
 
5.8%
c 9725
 
5.7%
g 7403
 
4.4%
o 7128
 
4.2%
Other values (10) 33646
19.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 169316
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 23340
13.8%
e 19002
11.2%
i 18370
10.8%
n 18095
10.7%
r 11874
 
7.0%
t 10962
 
6.5%
9771
 
5.8%
c 9725
 
5.7%
g 7403
 
4.4%
o 7128
 
4.2%
Other values (10) 33646
19.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 169316
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 23340
13.8%
e 19002
11.2%
i 18370
10.8%
n 18095
10.7%
r 11874
 
7.0%
t 10962
 
6.5%
9771
 
5.8%
c 9725
 
5.7%
g 7403
 
4.4%
o 7128
 
4.2%
Other values (10) 33646
19.9%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:46.910781image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

tech_tf_development_platform_hand_held
Real number (ℝ)

Constant  Missing  Zeros 

Distinct1
Distinct (%)< 0.1%
Missing353
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros9647
Zeros (%)96.5%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:47.014405image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-03T14:35:47.143406image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 9647
96.5%
(Missing) 353
 
3.5%
ValueCountFrequency (%)
0 9647
96.5%
ValueCountFrequency (%)
0 9647
96.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:47.254605image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:47.355775image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:47.449674image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.9 KiB
False
10000 
ValueCountFrequency (%)
False 10000
100.0%
2025-06-03T14:35:47.537723image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Distinct2
Distinct (%)1.4%
Missing9861
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean0.1510791367
Minimum0
Maximum1
Zeros118
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:47.657830image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3594212148
Coefficient of variation (CV)2.379026136
Kurtosis1.907809418
Mean0.1510791367
Median Absolute Deviation (MAD)0
Skewness1.969914874
Sum21
Variance0.1291836096
MonotonicityNot monotonic
2025-06-03T14:35:47.793208image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 118
 
1.2%
1 21
 
0.2%
(Missing) 9861
98.6%
ValueCountFrequency (%)
0 118
1.2%
1 21
 
0.2%
ValueCountFrequency (%)
1 21
 
0.2%
0 118
1.2%

project_prf_application_type_top_financial application area
Real number (ℝ)

Constant  Missing  Zeros 

Distinct1
Distinct (%)0.5%
Missing9812
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros188
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:47.934093image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-03T14:35:48.098357image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 188
 
1.9%
(Missing) 9812
98.1%
ValueCountFrequency (%)
0 188
1.9%
ValueCountFrequency (%)
0 188
1.9%

project_prf_application_type_top_client-server
Real number (ℝ)

Constant  Missing  Zeros 

Distinct1
Distinct (%)0.5%
Missing9804
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros196
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:48.225353image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-03T14:35:48.348977image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 196
 
2.0%
(Missing) 9804
98.0%
ValueCountFrequency (%)
0 196
2.0%
ValueCountFrequency (%)
0 196
2.0%
Distinct1
Distinct (%)0.5%
Missing9780
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros220
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-06-03T14:35:48.473231image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2025-06-03T14:35:48.620020image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 220
 
2.2%
(Missing) 9780
97.8%
ValueCountFrequency (%)
0 220
2.2%
ValueCountFrequency (%)
0 220
2.2%